Innovative Approaches to Modeling Alcohol Relapse

酒精复吸建模的创新方法

基本信息

批准号：
6560580
负责人：
Gordon ALAN Marlatt
金额：
$ 10.84万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2003
资助国家：
美国
起止时间：
2003-05-01 至 2005-04-30
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): The proposed research will use existing data from the Relapse Replication and Extension Project (RREP) to increase our understanding of the relapse process in individuals who have received treatment for an alcohol use disorder. This dataset includes pre- and post-treatment assessment of drinking behavior, background characteristics, and relapse precipitants in a group of 563 research participants, who were recruited from 15 treatment sites that offered a variety of alcoholism treatment approaches. Using a multi-deterministic framework, the relationship between background variables, risk and protective factors, and situational determinants will be examined with respect to post-treatment drinking outcomes. It is well-documented that a lack of effective coping responses increases relapse risk; and self-efficacy, outcome expectancies, and the abstinence violation effect, are cognitive factors that have been identified as important mediators in the return to heavy drinking following treatment. However, the relationship between these variables in the relapse process has not been clearly established. Focusing on the process of relapse, rather than evaluating relapse as a dichotomous event, the proposed research will examine trajectories of drinking behavior during the first year after treatment for an alcohol use disorder. Specifically, the first goal of the research is to further delineate the relationship between coping behavior, background characteristics, and cognitive factors in the prediction of these trajectories using advanced statistical models, including both catastrophe models and general growth mixture models. The second goal of the proposed research is to test the utility and appropriateness of these advanced modeling techniques in the prediction of post-treatment drinking outcomes. Gaining a better understanding of the relapse process has been a primary goal of addictive behaviors research for the past 30 years. The abundance of treatment outcome data for addictive behaviors makes the proposed research an important and cost-effective contribution to the advancement of our understanding of the relapse process.

描述（由申请人提供）：拟议的研究将使用复发复制和扩展项目（RREP）中的现有数据来增强我们对接受酒精使用障碍治疗的个人复发过程的理解。该数据集包括一组563名研究参与者的饮酒行为，背景特征和复发性沉淀物的治疗前和治疗后评估，他们是从15个提供了各种酒精中毒治疗方法的治疗部位招募的。使用多确定性框架，背景变量，风险和保护因素与情境决定因素之间的关系将在治疗后的饮酒结果方面进行研究。有充分记录的是，缺乏有效的应对反应会增加复发风险；自我效能感，预期结果和违反禁欲的效果是认知因素，在治疗后，已确定为重大饮酒的重要介体。但是，在复发过程中这些变量之间的关系尚未明确建立。拟议的研究专注于复发过程，而不是将复发作为二分事件，而是将饮酒行为在治疗酒精使用障碍后的第一年。具体而言，研究的第一个目标是进一步描述应对行为之间的关系，背景特征和认知因素在这些轨迹的预测中使用高级统计模型，包括灾难模型和一般生长混合物型号。拟议研究的第二个目标是测试这些先进的建模技术在预测后处理后的饮酒结果中。对复发过程有更好的了解一直是上瘾的主要目标过去30年的行为研究。成瘾行为的大量治疗结果数据使拟议的研究成为对我们对复发过程的理解的重要贡献。